Books & Videos

Table of Contents

Chapter: The Realm of Supervised Learning

Preprocessing Data Using Different Techniques

06m 38s

Label Encoding

02m 25s

Building a Linear Regressor

04m 25s

Regression Accuracy and Model Persistence

03m 41s

Building a Ridge Regressor

02m 41s

Building a Polynomial Regressor

02m 33s

Estimating housing prices

03m 45s

Computing relative importance of features

01m 54s

Estimating bicycle demand distribution

04m 35s

Chapter: Constructing a Classifier

Building a Simple Classifier

03m 40s

Building a Logistic Regression Classifier

04m 50s

Building a Naive Bayes’ Classifier

02m 11s

Splitting the Dataset for Training and Testing

01m 23s

Evaluating the Accuracy Using Cross-Validation

04m 6s

Visualizing the Confusion Matrix and Extracting the Performance Report

04m 14s

Evaluating Cars based on Their Characteristics

05m 12s

Extracting Validation Curves

02m 49s

Extracting Learning Curves

01m 37s

Extracting the Income Bracket

03m 36s

Chapter: Predictive Modeling

Building a Linear Classifier Using Support Vector Machine

04m 23s

Building Nonlinear Classifier Using SVMs

01m 47s

Tackling Class Imbalance

02m 53s

Extracting Confidence Measurements

02m 36s

Finding Optimal Hyper-Parameters

02m 16s

Building an Event Predictor

03m 45s

Estimating Traffic

02m 39s

Chapter: Clustering with Unsupervised Learning

Clustering Data Using the k-means Algorithm

03m 7s

Compressing an Image Using Vector Quantization

03m 37s

Building a Mean Shift Clustering

02m 35s

Grouping Data Using Agglomerative Clustering

03m 4s

Evaluating the Performance of Clustering Algorithms

02m 55s

Automatically Estimating the Number of Clusters Using DBSCAN

03m 34s

Finding Patterns in Stock Market Data

02m 34s

Building a Customer Segmentation Model

02m 21s

Chapter: Building Recommendation Engines

Building Function Composition for Data Processing

03m 25s

Building Machine Learning Pipelines

03m 54s

Finding the Nearest Neighbors

01m 56s

Constructing a k-nearest Neighbors Classifier

04m 18s

Constructing a k-nearest Neighbors Regressor

02m 43s

Computing the Euclidean Distance Score

02m 8s

Computing the Pearson Correlation Score

01m 55s

Finding Similar Users in a Dataset

01m 35s

Generating Movie Recommendations

02m 34s

Chapter: Analyzing Text Data

Preprocessing Data Using Tokenization

03m 0s

Stemming Text Data

02m 22s

Converting Text to Its Base Form Using Lemmatization

02m 11s

Dividing Text Using Chunking

02m 3s

Building a Bag-of-Words Model

02m 58s

Building a Text Classifier

04m 43s

Identifying the Gender

02m 17s

Analyzing the Sentiment of a Sentence

03m 9s

Identifying Patterns in Text Using Topic Modelling

04m 52s

Chapter: Speech Recognition

Reading and Plotting Audio Data

02m 34s

Transforming Audio Signals into the Frequency Domain

02m 9s

Generating Audio Signals with Custom Parameters

01m 45s

Synthesizing Music

02m 10s

Extracting Frequency Domain Features

02m 6s

Building Hidden Markov Models

02m 19s

Building a Speech Recognizer

03m 12s

Chapter: Dissecting Time Series and Sequential Data

Transforming Data into the Time Series Format

03m 7s

Slicing Time Series Data

01m 31s

Operating on Time Series Data

01m 42s

Extracting Statistics from Time Series

02m 29s

Building Hidden Markov Models for Sequential Data

04m 15s

Building Conditional Random Fields for Sequential Text Data

04m 27s

Analyzing Stock Market Data with Hidden Markov Models

02m 25s

Chapter: Image Content Analysis

Operating on Images Using OpenCV-Python

03m 7s

Detecting Edges

02m 47s

Histogram Equalization

02m 30s

Detecting Corners and SIFT Feature Points

03m 46s

Building a Star Feature Detector

01m 34s

Creating Features Using Visual Codebook and Vector Quantization

04m 10s

Training an Image Classifier Using Extremely Random Forests

02m 30s

Building an object recognizer

01m 53s

Chapter: Biometric Face Recognition

Capturing and Processing Video from a Webcam

01m 58s

Building a Face Detector using Haar Cascades

02m 40s

Building Eye and Nose Detectors

01m 54s

Performing Principal Component Analysis

02m 17s

Performing Kernel Principal Component Analysis

02m 2s

Performing Blind Source Separation

02m 16s

Building a Face Recognizer Using a Local Binary Patterns Histogram

04m 14s

Chapter: Deep Neural Networks

Building a Perceptron

02m 40s

Building a Single-Layer Neural Network

01m 37s

Building a deep neural network

02m 19s

Creating a Vector Quantizer

01m 40s

Building a Recurrent Neural Network for Sequential Data Analysis

02m 23s

Visualizing the Characters in an Optical Character Recognition Database

01m 48s

Building an Optical Character Recognizer Using Neural Networks

02m 28s

Chapter: Visualizing Data

Plotting 3D Scatter plots

02m 42s

Plotting Bubble Plots

01m 16s

Animating Bubble Plots

01m 56s

Drawing Pie Charts

01m 33s

Plotting Date-Formatted Time Series Data

01m 33s

Plotting Histograms

01m 5s

Visualizing Heat Maps

01m 15s

Animating Dynamic Signals

02m 6s